Integrated circuits, communication units and methods of cancellation of intermodulation distortion

ABSTRACT

A wireless communication unit includes a transmitter, a receiver, a selectivity element and a baseband processing module. The receiver has at least one summation module arranged to add a cancellation signal to the quadrature baseband receive signal. a baseband processing module arranged to: receive the quadrature baseband transmit signal and quadrature baseband receive signal; apply independent gain and phase adjustments to quadrature portions of the quadrature baseband transmit signal, based on at least one signal component of the quadrature baseband receive signal, to form independent cancellation signals; and apply the independent cancellation signals to the at least one summation module.

FIELD OF THE INVENTION

The field of this invention relates to integrated circuits,communication units and methods of cancellation of intermodulationdistortion. The invention is applicable to, but not limited to, secondorder intermodulation product distortion cancellation in integratedcircuits and wireless communication units.

BACKGROUND OF THE INVENTION

For many years frequency division duplex (FDD) and time division duplex(TDD) have been the two methods of choice for handling uplink (UL) anddownlink (DL) transmissions in wireless systems. FDD uses two differentfrequencies for the UL and DL thereby separating them in frequencywhereas TDD utilises a single frequency for both UL and DL signals andseparates them in time. Therefore, in order to meet the performancerequirements of a number of telecommunications standards, integratedcircuits (ICs) and/or communication units have been designed to utilisefrequency division duplex (FDD) techniques as a mechanism to separateUL/DL transmit and receive communications.

As a consequence, and particularly at typical wireless communicationfrequencies where the transmit (and therefore receive) frequency is veryhigh, such as in the 1 GHz frequency region in the third generation (3G)wideband code division multiple access (WCDMA) standard, it is knownthat interference is caused by poor isolation between the transmittedand received signals at these very high frequencies within the ICs orcommunication units. Here, the transmit signal leaks through the duplexfilter and mixes via the mechanism of second order distortion within thereceive mixer to baseband, thereby resulting in degraded receive signalto noise ratio (SNR) performance. This causes an effectivedesensitization of the receiver. The problem becomes critical when thetransmitter is operating at, or near, the transmitter's maximum transmitpower capability whilst the receiver is operating at, or near, itsminimum receive power capability, referred to as the receiver's‘sensitivity’. In this scenario, such 2^(nd) order intermodulationproducts can ‘desense’ the radio and lead to bit-error-rate (BER)failure. Second order intermodulation distortion (IM2 or IIP2) occurswhen two signals mix with each other through a second order nonlinearityto produce an intermodulation product at the sum and differencefrequencies of the two interferers.

FIG. 1 schematically illustrates known circuitry and a cause of such2^(nd) order intermodulation product interference effects in a highfrequency communication unit 100. The high frequency communication unit100 comprises digital baseband ‘I’ and ‘Q’ signals 102 being input to atransmit digital-to-analogue converter (TX DAC) 105, where the digitalbaseband ‘I’ and ‘Q’ signals 102 are converted to analogue baseband ‘I’and ‘Q’ signals and filtered in low pass filter (LPF) 110. The filteredbaseband signals are then up-converted in frequency using a mixer stage115 coupled to a local oscillator (LO) 120, such that the filteredbaseband signals are translated in frequency to the frequency of the LOsignal provided the LO 120. The up-converted signal output from themixer stage 115 is input to a power amplifier (PA) 125, where it isamplified to a sufficiently high radio frequency level to be radiatedfrom antenna 135. The antenna 135 is coupled to a (transmit (Tx)/receive(Rx)) duplex filter 130 which attempts to attenuate signals receivedfrom the transmit path from entering the communication unit's receivepath. However, given the limitations of filtering technology at suchhigh radio frequencies, a significant amount of the transmit signal isleaked 140 into the receiver path.

Thus, in the receive path, the antenna 135 and Tx/Rx duplex filter 130route received high frequency signals to a low noise amplifier (LNA)145. The amplified high frequency signal is input to a quadraturedown-mixer 150, which down-converts the amplified signal by multiplyingit with a quadrature shifted 155 local oscillator (LO) signal that isfed from a LO source 160. The outputs from the quadrature down-mixer 150are at baseband frequencies, such that low-pass or band-pass filtering(LPF/BPF) 165 can be used to remove or attenuate undesired signals inthe frequency domain. The baseband signals may be at a low frequency(LF) signal, a very low intermediate frequency (VLIF) signal or even aDC (zero IF) signal. Baseband (analogue) filtered signals are thendigitised in the receive analogue-to-digital converter (RX ADC) 170 andfiltered again to remove quantization effects in filter 175. Graph 185illustrates how the performance of the receiver is de-sensitised (oftenreferred to as ‘desense’) by the leakage of the transmit signal into thereceive path, with most of the desense effect occurring in the receivedown-mixer stage. The performance reduction is measured in terms of‘desense’ and ultimately bit error rate (BER) and is due to a presenceof IMD2 products in the baseband signal.

The classical solution to minimising the level of transmit signalleaking into the receive path uses a surface acoustic wave (SAW) filter.However, the use of SAW filters is no longer acceptable due to theirlarge size and high cost factors, coupled to the ever-increasing need tominimise product cost and size, particularly in the mobile telephonehandset business.

One attempted solution has been to use an integrated narrow bandwidth,tuneable band-pass or notch type filter, to replace the functionality ofthe SAW filter. However, this solution suffers from the need to usemultiple lumped element inductors.

A yet further alternative approach is to employ a calibration schemethat trims the receive down-mixer operation for maximum IIP2 acrossprocess, voltage and temperature (PVT) variation. However, it isbelieved that this approach may not be effective, as analogue radiofrequency designs do not cope well across PVT. Furthermore, there is aconcern that the addition of a dedicated trimming port could potentiallycompromise other key RF metrics.

One known example of cancellation of second order intermodulationproducts is illustrated in FIG. 2. As shown, the digital baseband ‘I’and ‘Q’ signals 102 are also input to an adaptive intermodulationdistortion (IMD) cancellation function 215. The IMD cancellationfunction 215 is arranged to provide a digital estimate (in signals 220,225) of the transmitter second order intermodulation distortioncomponents of the communication unit. Thereafter, the digital estimate(in signals 220, 225) of the transmit second order intermodulationdistortion components are subtracted from the signals output from filter175 in subtraction blocks 230, 235, thereby (in principle) removing aportion of the second order intermodulation distortion components thathave been created in the receive path as a result of leakage of thetransmit signal through the duplex filter 130. In this manner, theestimation of interference is based on a correlated reference. Thus, thetechnique of FIG. 2 generates an error signal after DC correction of thereceive signal, and uses this error signal to train the adaptiveinterference cancellation in IMD cancellation function 215. Thereafter,the cancellation is adapted so as to minimise the mean squared power ofthe estimation error.

There are some disadvantages that exist in the related art, such as theselectivity of the receiver performance (when a bandwidth (BW) is, say,<100 Hz) comes at a disadvantage of too slow a settling time, forexample due to any averaging technique used. Hence, a designer inconsidering DC correction techniques is confronted with a trade offbetween selectivity versus settling time. A further disadvantage thatexists in the related art is that a common ‘I’ and ‘Q’ path and hence asingle gain stage are used to control the cancellation signal. A yetfurther disadvantage that exists in the related art is that a fixed (andtherefore rigid) value of adaptation rate is selected to work across thepower range of the communication unit.

Thus, a need exists for improved integrated circuits, communicationunits and methods of cancellation therefor.

SUMMARY OF THE INVENTION

Accordingly, the invention seeks to mitigate, alleviate or eliminate oneor more of the above mentioned disadvantages singly or in anycombination. Aspects of the invention provide improved integratedcircuits, communication units and methods therefor as described in theappended claims.

According to a first aspect of the invention, there is provided awireless communication unit comprises a transmitter arranged to processa quadrature baseband transmit signal to produce a first radio frequencysignal for wireless transmission. The wireless communication unitcomprises a receiver arranged to receive a second radio frequency signaland convert the second radio frequency signal to a quadrature basebandreceive signal, wherein the receiver comprises at least one summationmodule arranged to add a cancellation signal to the quadrature basebandreceive signal. The wireless communication unit comprises a selectivityelement that is arranged to couple the transmitter and the receiver toan antenna, such that a reduced portion of the first radio frequencysignal is introduced into the second radio frequency signal therebycreating a second order inter-modulation distortion component in thebaseband receive signal. The wireless communication unit furthercomprises a baseband processing module arranged to: receive thequadrature baseband transmit signal and quadrature baseband receivesignal; apply independent gain and phase adjustments to quadratureportions of the quadrature baseband transmit signal, based on at leastone signal component of the quadrature baseband receive signal, to formindependent cancellation signals; and apply the independent cancellationsignals to the at least one summation module.

In this manner, an enhanced second order intermodulation model, withindependent phase and gain adjustment, may be generated in order toprovide a more accurate cancellation of IMD2 products.

According to an optional feature of the invention, the basebandprocessing module may comprise a plurality of independent adaptivefilters. The plurality of independent adaptive filters may comprisemulti-tap finite impulse response (FIR) filters arranged to compensatefor a mismatch error between the quadrature baseband receive signal andthe quadrature baseband transmit signal.

According to an optional feature of the invention, the wirelesscommunication unit may comprise a power measurement module operablycoupled to the adaptive estimator module and arranged to measure anon-channel power level of the baseband receive signal. The adaptiveestimator module comprises a baseband processing module arranged todetermine an adaptation rate to be used by the adaptive estimator modulein generating the cancellation signal based on the measured on-channelpower level of the baseband receive signal. In this manner, a mechanismis described that provides an automatic regulation of adaptation rate toreduce second order intermodulation distortion.

According to an optional feature of the invention, the basebandprocessing module may be arranged to ignore uncorrelated noisecomponents, such that the cancellation signal cancels second orderintermodulation distortion component.

According to an optional feature of the invention, the receiver maycomprise an analogue-to-digital converter operably coupled to thesummation module. The receiver may further comprise a digital filterlocated in the receiver and arranged to filter signals output from thesummation module; and the adaptive estimator module may be arranged toreceive the output filtered signals and the baseband transmit signal andproduce the cancellation signal based thereon. In this manner, thecancellation node may be appropriately partitioned across the basebandfiltering elements.

According to an optional feature of the invention, the digital filtermay be a digital adjacent channel filter, which may comprise a matchingfilter.

According to an optional feature of the invention, the wirelesscommunication unit may further comprise a controller module arranged toperform cross-correlation of at least one tap of each of the firstbaseband transmit signal and the cancellation signal to produce an errorsignal that is representative of a time difference therebetween. Thewireless communication unit may further comprise a controllable delayelement operably coupled to the controller module and arranged to usethe error signal to set a time delay applied to at least one from agroup of: the first baseband transmit signal, the cancellation signal.In this manner, a self-tuning time alignment system may be obtained.

According to an optional feature of the invention, the controller modulemay be arranged to perform cross correlation between two signalsevaluated at a number of lag points.

According to an optional feature of the invention, the controller modulemay be arranged to adjust the controllable delay element until the errorsignal is at a minimum.

According to a second aspect of the invention, there is provided anintegrated circuit for a wireless communication unit. The integratedcircuit comprises a transmitter arranged to process a quadraturebaseband transmit signal to produce a first radio frequency signal forwireless transmission. A receiver is arranged to receive a second radiofrequency signal comprising a reduced portion of the first radiofrequency signal and convert the second radio frequency signal to aquadrature baseband receive signal, wherein the receiver comprises atleast one summation module arranged to add a cancellation signal to thequadrature baseband receive signal, and wherein the reduced portion ofthe first radio frequency signal creates a second order inter-modulationdistortion component in the baseband receive signal. A basebandprocessing module is arranged to receive the quadrature basebandtransmit signal and quadrature baseband receive signal; applyindependent gain and phase adjustment to quadrature portions of thequadrature baseband transmit signal, based on at least one signalcomponent of the quadrature baseband receive signal, to form independentcancellation signals; and apply the independent cancellation signals tothe at least one summation module.

According to a third aspect of the invention, there is provided a methodfor reducing a second order inter-modulation distortion component in awireless communication unit. The method comprises processing aquadrature baseband transmit signal to produce a first radio frequencysignal for wireless transmission; and receiving a second radio frequencysignal comprising a reduced portion of the first radio frequency signalthat creates a second order inter-modulation distortion component in thebaseband receive signal. The method further comprises converting thesecond radio frequency signal to a quadrature baseband receive signal;applying independent gain and phase adjustments to quadrature portionsof the quadrature baseband transmit signal, based on at least one signalcomponent of the quadrature baseband receive signal, to form independentcancellation signals; and adding the independent cancellation signals tothe quadrature baseband receive signal to reduce the second orderinter-modulation distortion component.

According to a fourth aspect of the invention, there is provided acomputer program product comprising executable program code for reducinga second order inter-modulation distortion component in a wirelesscommunication unit. The executable program code is operable forprocessing a quadrature baseband transmit signal to produce a firstradio frequency signal for wireless transmission; and receiving a secondradio frequency signal comprising a reduced portion of the first radiofrequency signal that creates a second order inter-modulation distortioncomponent in the baseband receive signal. The executable program code isfurther operable for converting the second radio frequency signal to aquadrature baseband receive signal; applying independent gain and phaseadjustments to quadrature portions of the quadrature baseband transmitsignal, based on at least one signal component of the quadraturebaseband receive signal, to form independent cancellation signals; andadding the independent cancellation signals to the quadrature basebandreceive signal to reduce the second order inter-modulation distortioncomponent.

These and other aspects of the invention will be apparent from, andelucidated with reference to, the embodiments described hereinafter.

BRIEF DESCRIPTION OF THE DRAWINGS

Further details, aspects and embodiments of the invention will bedescribed, by way of example only, with reference to the drawings.Elements in the figures are illustrated for simplicity and clarity andhave not necessarily been drawn to scale. Like reference numerals havebeen included in the respective drawings to ease understanding.

FIG. 1 illustrates a high level block diagram of a communication unitillustrating a known problem with second order intermodulationdistortion.

FIG. 2 illustrates a high level block diagram of a communication unitillustrating a known potential solution to the second orderintermodulation distortion problem.

FIG. 3 illustrates a high level block diagram of an examplecommunication unit adapted to implement embodiments of the invention.

FIG. 4 illustrates a more detailed functional block diagram of anexample communication unit adapted to implement embodiments of theinvention.

FIG. 5 illustrates examples of a construction of a second orderintermodulation distortion (IMD2) model.

FIG. 6 illustrates an example of a receiver baseband processing model ofthe receiver path of FIG. 4.

FIG. 7 illustrates an example of a self-tuning delay mechanism, forexample to complement a fixed delay synchronisation technique.

FIG. 8 illustrates a typical computing system that may be employed toimplement signal processing functionality in embodiments of theinvention.

DETAILED DESCRIPTION

Examples of the invention will be described in terms of a wirelesscommunication unit that supports code division multiple accesscommunications. However, it will be appreciated by a skilled artisanthat some concepts herein described may be embodied in any type ofwireless communication unit and may, thus, not be limited to a CDMAcommunication unit.

Referring first to FIG. 3, a block diagram of a wireless communicationunit (sometimes referred to as a mobile subscriber unit (MS) in thecontext of cellular communications or user equipment (UE) in terms of a3^(rd) generation partnership project (3GPP) communication system) isshown, in accordance with example embodiments of the invention. Thewireless communication unit 300 contains an antenna 302 preferablycoupled to a duplex filter or antenna switch 304 that provides isolationbetween receive and transmit chains within the wireless communicationunit 300.

The receiver chain, as known in the art, includes receiver front-endcircuitry 306 (effectively providing reception, filtering andintermediate or base-band frequency conversion). The front-end circuitry306 is serially coupled to a signal processing module 308. An outputfrom the signal processing module 308 is provided to a suitable outputdevice 310, code power indicator (RSCP) circuitry 312, which in turn iscoupled to a controller 314 that maintains overall subscriber unitcontrol. The controller 314 may therefore receive bit error rate (BER)or frame error rate (FER) data from recovered information. Thecontroller 314 is also coupled to the receiver front-end circuitry 306and the signal processing module 308 (generally realised by a digitalsignal processor (DSP) 330). The controller is also coupled to a memorydevice 316 that selectively stores operating regimes, such asdecoding/encoding functions, synchronisation patterns, code sequences,RSSI data and the like.

In accordance with examples of the invention, the memory device 316stores filter information, such as adaptive filter co-efficients, lineartransmit-receive gain values, time alignment settings, adaptation ratevalues, dc filter tuning rate, etc. At a higher level the memory device316 may stores will be the whole state machine data/code, whichconfigures and controls the lower level h/w. Thus, data contained in thememory device 316 may be used by the wireless communication unit 300 andprocessed by signal processing module 308. Furthermore, a timer 318 isoperably coupled to the controller 314 to control the timing ofoperations (transmission or reception of time-dependent signals) withinthe wireless communication unit 300.

As regards the transmit chain, this essentially includes an input device320, such as a keypad, coupled in series through transmitter/modulationcircuitry 322 and a power amplifier 324 to the antenna 302. Thetransmitter/modulation circuitry 322 and the power amplifier 324 areoperationally responsive to the controller 314.

The signal processor module in the transmit chain may be implemented asdistinct from the processor in the receive chain. Alternatively, asingle processor module 308 may be used to implement processing of bothtransmit and receive signals, as shown in FIG. 3. Clearly, the variouscomponents within the wireless communication unit 300 can be realised indiscrete or integrated component form, with an ultimate structuretherefore being merely an application-specific or design selection.

Referring now to FIG. 4, a more detailed functional diagram of anexample of a wireless communication unit 400 is illustrated. Thewireless communication unit 400 comprises digital baseband ‘I’ and ‘Q’signals 402, 404 being input to a transmit digital-to-analogue converter(TX DAC) 406, where the digital baseband ‘I’ and ‘Q’ signals 402, 404are converted to analogue baseband ‘I’ and ‘Q’ signals and filtered inlow-pass analogue anti-aliasing filter 408. The filtered basebandsignals are then up-converted in frequency using a mixer stage 410coupled to a local oscillator (LO) 412, such that the filtered basebandsignals are translated in frequency to the frequency of the LO signalprovided the LO 412. The up-converted signal output from the mixer stage410 is input to a power amplifier 414, where it is amplified to asufficiently high radio frequency level to be radiated from antenna 418.The antenna 418 is coupled to a (transmit (Tx)/receive (Rx)) duplexfilter 416, which attempts to attenuate signals received from thetransmit path from entering the communication unit's receive path.However, given the limitations of filtering technology at such highradio frequencies, a significant amount of the transmit signal may beleaked into the receiver path. In the receive path, the antenna 418 andTx/Rx duplex filter 416 route received high frequency signals to a lownoise amplifier (not shown). The amplified high frequency signal isinput to a quadrature down-mixer 420, which down-converts the amplifiedsignal by multiplying it with a quadrature shifted 422 local oscillator(LO) signal that is fed from a LO source 424. The outputs from thequadrature down-mixer 420 are at baseband frequencies, such thatanalogue low-pass or band-pass filter (LPF/BPF) 426 can be used toremove (or substantially attenuate) undesired adjacent channelinterfering (ACI) signals in the frequency domain.

The baseband signals may be at a low frequency (LF) signal, a very lowintermediate frequency (VLIF) signal or even a DC (zero IF) signal.Baseband (analogue) filtered signals are then digitised in the receiveanalogue-to-digital converter (RX ADC) 428.

In accordance with one example embodiment, the digital transmit, ‘I’ and‘Q’ samples 402, 404 are tapped off prior to the transmit DAC 406 andfiltered by ĝ(n) filter 436, where ĝ(n) is arranged to be a model of thecomposite (e.g. the digital plus analogue) filtering that is presentalong the transmit path between the tap-off, reference point and thetransmit radio frequency port (at the antenna 418). In one exampleembodiment, the ĝ(n) filter 436 is a fixed, predetermined filter,assumed to be known apriori. In this example embodiment, the modulus oramplitude, squared; I²+Q², of the filtered transmit baseband signals isthen calculated in squaring module 438 and delayed by a programmabledigital tapped delay line module, z^(−{circumflex over (D)}), 440. Onepurpose of programmable digital tapped delay line module,z^(−{circumflex over (D)}), 440 is to synchronise the digital estimateto the actual IMD2 product at the point of cancellation.

In one example embodiment, the transmit-to-receive group delay variationarising from the associated analogue filter variation may besufficiently low that a fixed programmable delay of resolution betterthan, say, a ¼ chip period could be sufficient. Accordingly, the delayline value {circumflex over (D)} can be set by an upper layer ofconfiguration firmware or software. In alternative examples, the delayline value {circumflex over (D)} may be set using programmable delayelements.

The synchronised amplitude squared signal output from squaring module438 is then filtered in digital filter 442 by ĥ(n), which models thecomposite baseband filtering along the receive path, including, forexample, analogue receive filter(s), ADC signal transfer dynamics, anyCIC decimation filters, any digital compensation/decimation modules andany receive channel square root raised cosine (SRRC) filter. As in thetransmit case, ĥ(n) may be configured as a predetermined, fixed filter,whose value is determined off-line from laboratory characterised data.

The synchronized, filtered amplitude squared signal is then scaled inscaling module 446 by the deterministic gain value ĝ_(txrx), whichrepresents the known apriori gain from the digital TX tap-off point tothe digital cancellation point. Scaling module 446, scaling thesynchronized, filtered amplitude squared signal by ĝ_(txrx), comprisesthe known gain along the transmit path from the digital baseband to thetransmitter port of the duplexer (or duplex filer) 416, the (worst case)duplexer transmit-receive isolation, and front-end receiver (linear)gain (for example dominated by the LNA (not shown) and the known gainfrom the down-mixer stage 420 to the digital baseband cancellation point(e.g. predominantly the gain from AGC gain (also not shown for claritypurposes)). In one example embodiment, this gain may be set dynamicallyby an upper layer of firmware or software, based on the actual gainthrough the transmit path (which in turn is based on the transmit targetoutput power) and the AGC setting.

The final stage of the cancellation path compromises two, low order,adaptive finite impulse response (FIR) filters, ĥ_(I)(n) 448 andĥ_(Q)(n) 449 for the ‘I’ and ‘Q’ paths respectively. An FIR filter is atype of digital filter where the filter's impulse response to aKronecker delta input, is finite because it settles to zero in a finitenumber of sample intervals. The impulse response of an Nth-order FIRfilter lasts for N+1 samples, and then dies to zero. The purpose of theadaptive FIR filters 448, 449 is primarily to model the actual IMD2 gainthrough the receive mixer-stages, in addition to reducing or removingany gain uncertainty associated with the predetermined scalar gainĝ_(txrx), that is associated with the estimate of the duplexertransmit-receive isolation and the remaining gain through the transmitand receive paths. In addition, in one example, the adaptive FIRfilters, ĥ_(I)(n) 448 and ĥ_(Q)(n) 449 are also responsible forminimizing any phase uncertainty and residual time misalignment accruingfrom the mis-modelling of the transmit and receive filters (ĝ(n) 436 andĥ(n) 442 respectively). Furthermore, in one example, the provision oftwo independent adaptive FIR filters, ĥ_(I)(n) 448 and ĥ_(Q)(n) 449 mayallow for a more complex IMD2 model, beyond that of a standard gainrelationship. In particular, such a structure may facilitate the ‘I’ and‘Q’ paths having an independent IMD2 phase response, (whereas theclassical or conventional filter model allows for only an independentgain response and assumes a common phase response along both paths).

In this example, the outputs Î_(IMD2) 450 and {circumflex over(Q)}_(IMD2) 452 of the adaptive FIR filters, ĥ_(I)(n) 448 and ĥ_(Q)(n)449, provide the complex baseband estimate of the IMD2 product, which issubtracted from the actual received ‘I’ and ‘Q’ values in the receivepath in subtraction modules 430, as shown, to generate a cancelled (orcorrected) complex signal. The cancelled (or corrected) complex signalis filtered in digital adjacent channel interference (ACI) filter 432.

In one example embodiment, the filtered cancelled (or corrected) complexsignal also becomes the error for the adaptive update equation.

Modelling of IMD2 Factors Using Independent ‘I’ and ‘Q’ Adjustments:

An important factor in the accurate implementation of the adaptivecanceller is the modelling of the IMD2 path from the transmit basebandcircuitry to the receive baseband circuitry. Referring now to FIG. 5, anexample of the construction of a second order intermodulation distortion(IMD2) basic model 500 to achieve this is presented.

Due to finite isolation of the duplexer 416 of FIG. 4, a certain amountof the transmit power will leak through to the receive port. Referringto FIG. 5, the leaked transmit signal 505 can be expressed as:A(t)cos {ω_(tx)t+φ_(tx)(t)}  [1]where:

A is the envelope or amplitude modulated component of the transmit radiofrequency signal,

ω_(tx) is the carrier frequency of the transmit radio frequency signal,and

φ_(tx) is the phase modulated component of the transmit radio frequencysignal.

Phase offsets, carrier offsets, phase errors and all other impairmentsand transmitter imperfections have been ignored for the purpose of thisexplanation of the ‘basic’ model 500. Parasitic coupling paths of thetransmit to both the radio frequency input port and the local oscillatorport of the Rx mixer-stage in addition to any other parasitic couplingpath produces, in the leakage signal, self mixing. This gives rise tothe characteristic squaring or second order effect, which in effectresults in an output composed of a baseband signal that is proportionalto:A²/2  [2]and a radio frequency term at twice the transmit carrier frequencyproportional to:0.5A²(t)cos {2ω_(tx)t+2φ_(tx)(t)}.  [3]

The receiver analogue channel filters 555, 560 remove the radiofrequency component, which leaves the baseband term proportional to theleaked transmit amplitude modulation (AM) level, squared. The phasecomponent of the transmit leakage is effectively stripped off by thesquaring effect in squaring module 530 with the amount of amplitudemodulated squared power level that mixes to baseband being determined bythe IIP2 of the mixer-stage. The weighting or gain terms, a_(2I) 540 anda_(2Q) 535 are introduced for both the ‘I’ and ‘Q’ path to model thisscaling effect, resulting in the basic expressing for the IMD2 term:IMD₂ =A ²(a _(2I) +ja _(2Q))  [4]

The weighting or ‘a2 coefficients’ can be reconciled with theconventional definition of IIP2, as illustrated in equation [5]:IIP₂(dBVrms)=−20 log₁₀√{square root over (2)}|a ₂|  [5]where:a ₂=√{square root over (a _(2I) ² +a _(2Q) ²)}.  [6]

Thus, once the actual mixer-stage IIP2 performance has been calculated,it is also possible to calculate the equivalent ‘a2’ coefficients.Furthermore, as the radio frequency envelope is simply a scaled, delayand/or filtered version of the original transmit amplitude modulationsignal, in principle, and once this scaling and filtering is known, itis possible to evaluate the amplitude modulated squared term and thecorresponding instantaneous IMD2 time series. Thus, the ‘basic’ model500 and equations [4] to [6] encapsulate the conventional definition andmodel of IM2, which is limited. The inventor has recognised andappreciated that in some instances, the basic model may be insufficientand instead of being limited to a pure gain along the ‘I’ and ‘Q’ IM2paths independent filters may be used.

Referring now to the second diagram in FIG. 5, an example of theconstruction of a second order intermodulation distortion (IMD2)extended model 590 is presented. In particular, the extended model 590addresses any potentially inadequate calculation of the common phaseresponse along both the ‘I’ and ‘Q’ IMD2 path. The example extendedmodel includes an independent, low order FIR structure 565, 570, whichhas been incorporated on each respective path to allow a different phaseresponse along each path. As shown in the second diagram of FIG. 5, thesingle ‘a2’ coefficient is now replaced by a low order FIR structure565, 570, such that the past and present amplitude modulated squaredvalues are used in the evaluation of the instantaneous IMD2. Moreover,in one example, the coefficients for the respective FIR taps areconfigurable in order to track out uncertainty and time-varyingmodelling errors that are associated with the transmit baseband analogueanti-imaging and receive filtering. The low order FIR structure 565, 570are adaptive and updated dynamically and are, for example, of an FIRform:

$\begin{matrix}{{{\hat{H}}_{I}\left( z^{- 1} \right)} = {\sum\limits_{m = 0}^{M - 1}{{{\hat{h}}_{I}(m)}z^{- m}}}} & \lbrack 7\rbrack\end{matrix}$

Using this structure, the extended IMD2 model becomes:

$\begin{matrix}{{{IMD}_{2}(n)} = {{\sum\limits_{m = 0}^{M - 1}{{{\hat{h}}_{I}(m)}{A^{2}\left( {n - m} \right)}}} + {j{\sum\limits_{m = 0}^{M - 1}{{{\hat{h}}_{Q}(m)}{A^{2}\left( {n - m} \right)}}}}}} & \lbrack 8\rbrack\end{matrix}$

It is noted that the classical (basic) IMD2 model is a special case ofthe extended model in equation [8], where M=1, such that:â _(2I) =ĥ _(I)(0) andâ _(2Q) =ĥ _(Q)(0)

Referring now to FIG. 6, an example of a receiver baseband processingmodel 600, of the receiver path of FIG. 4, is illustrated. The receiverbaseband processing model 600 comprises a squaring module 602, whichequates to the parasitic coupling path effects between the radiofrequency port and the local oscillator port of the receiver mixer-stage420 of FIG. 4. The squaring effect results from self mixing of theleakage signal, as previously described with respect to FIG. 5. Thereceiver baseband processing model 600 further comprises two independentadaptive FIR filters, ĥ_(I)(n) 604 and ĥ_(Q)(n) 606, which may allow fora more complex receiver baseband processing IMD2 model, beyond that of astandard gain relationship. The receiver baseband processing model 600further comprises respective ‘I’ and ‘Q’ analogue adjacent channelfilter 426, followed by analog AGC stages 605 (not shown in FIG. 4),which are also coupled to ΣΔ-ADC (with associated signal shaping) 428.The receiver baseband processing model 600 further comprises respective‘I’ and ‘Q’ a decimator containing a CIC filtering (and any associatedcompensation/decimation stage) 620 followed by respective digitaladjacent channel interference filters 432 and the digital SRRC channelfilters 625 (also not shown in FIG. 4).

For simplicity purposes only, the DC or offset correction system/modelhas not been included in the exemplary models of FIG. 5 or FIG. 6.Although offsets have a profound effect on the canceller performance,and in particular the estimator that trains or adapts the IMD2 FIRcoefficients, the DC effect is treated separately and is not modelledexplicitly.

In one example, it is assumed that the analogue adjacent channelinterference filters 426 and analog AGC 610 are matched, inasmuch as itis assumed that their differential mismatch is negligible. In thisregard, it is possible to simplify the model of FIG. 6 further, to apoint where a common gain and filter are used to represent the basebandprocessing.

Thus, the known art of US2008/0232268 discloses a receiver chain thatproposes a use of a common digital ‘I’ and ‘Q’ processing path.Consequently, the prior art of US2008/0232268 proposes the use of asingle gain stage. Thus, in one example, as described above, the presentinvention discloses a wireless communication unit that solves a problemof how to provide a more accurate cancellation of IMD2 products byprovision of a digital processing chain that accommodates independent2^(nd) order ‘I’ and ‘Q’ paths. In one example wireless communicationunit, the baseband signals are quadrature baseband signals. The examplewireless communication unit comprises an adaptive estimator module thatcomprises a baseband processing module arranged to: receive thequadrature baseband transmit signal and quadrature baseband receivesignal. The adaptive estimator module is further arranged to applyindependent gain and phase adjustment to quadrature portions of thequadrature baseband transmit signal, based on at least one signalcomponent of the quadrature baseband receive signal, to form independentcancellation signals. The adaptive estimator module is further arrangedto apply the independent cancellation signals to the summation module.

Adaptive Estimator

In one example embodiment, the cancellation of second orderintermodulation distortion components is performed by an adaptiveestimator, for example in a form of a least mean square (LMS) adaptiveestimator. A general form of the LMS equation may be provided by:

$\begin{matrix}{{\hat{\theta}(n)} = {{\hat{\theta}\left( {n - 1} \right)} - {\mu\frac{\partial{ɛ(n)}}{\partial{\hat{\theta}\left( {n - 1} \right)}}{ɛ(n)}}}} & \lbrack 9\rbrack\end{matrix}$where:

{circumflex over (θ)}(n) is the M×1 row vector of parameter estimates atthe m^(th) sample index; and

M is the number of parameters to be estimated,

ε is the estimation error, and

μ is the step-size or adaptation rate that may be chosen to trade offspeed of convergence versus noise rejection.

The basic principle of applying equation [9] to a specific case of IMD2cancellation is illustrated in FIG. 4, where the cancelled outputbecomes the estimation error which is fed back to the LMS updateequation. To maximize the estimation error signal (e.g. thesignal-to-noise ratio (SNR)) the feed back point may be taken after thereceive digital channel—square root raised cosine (SRRC) filter, leadingto the estimation error for the ‘I’ path (noting the ‘Q’ path has asimilar expression) of:ε_(I)(n)=I(n)−Î _(IMD2)(n)  [10]

The generic derivative term ∂ε(n)/∂{circumflex over (θ)}(n−1) becomesfor the IMD2 cancellation application

$\begin{matrix}{\frac{\partial{ɛ_{I}(n)}}{\partial{{\hat{h}}_{I}\left( {n - 1} \right)}} = {- \frac{\partial{{\hat{I}}_{{IMD}\; 2}(n)}}{\partial{{\hat{h}}_{I}\left( {n - 1} \right)}}}} & \lbrack 11\rbrack\end{matrix}$

Hence, the estimated IMD2 term (for the ‘I’ path) is provided by:

$\begin{matrix}{{{\hat{I}}_{{IMD}\; 2}(n)} = {{\hat{g}}_{txrx}{\sum\limits_{m = 0}^{M_{I} - 1}{{{\hat{h}}_{I}\left( {{m,n} - 1} \right)}{A^{2}\left( {n - m} \right)}}}}} & \lbrack 12\rbrack\end{matrix}$where:

the AM-squared term, A² is the output of the fixed, deterministic filtermodel line-up, as shown in FIG. 4.

In one example, the term ĥ_(I)(m) may be replaced by ĥ_(I)(m,n−1),where, as before, m is the m^(th) coefficient of the FIR filter, whilstthe additional (time) index, n−1 is now included to signify theunderlying time-varying nature of the filter arising from the adaptationor adjustment by the LMS algorithm. Thereafter, the derivative termreduces to:

$\begin{matrix}{\frac{\partial{ɛ_{I}(n)}}{\partial{{\hat{h}}_{I}\left( {n - 1} \right)}} = {{- {A^{2}(n)}}{\hat{g}}_{txrx}}} & \lbrack 13\rbrack\end{matrix}$

Here ĥ(n−1) is a M×1 row vector of FIR taps or coefficient estimates(corresponding to the vector of parameter estimates, {circumflex over(θ)}(n−1) in the generic LMS equation), as distinct from the scalar orindividual coefficient, ĥ(m,n−1) at time index n−1. Similarly, A²(n) isa M×1 row vector, whilst A²(n−m) is the associated m^(th) entry of thatvector. The gain term ĝ_(txrx) is a positive scalar value and in oneexample does not include any directional information in the form ofphase or sign. Furthermore, removing the gain term to give thenormalized derivative term in equation [14]:

$\begin{matrix}{\frac{\partial{ɛ_{I}(n)}}{\partial{{\hat{h}}_{I}\left( {n - 1} \right)}} = {- {A^{2}(n)}}} & \lbrack 14\rbrack\end{matrix}$facilitates a more efficient implementation as its numerical range canbe limited to a positive scalar value between ‘0’ and ‘1’. Substitutingthis term back into the LMS equation provides the update algorithm forthe m^(th) coefficient:ĥ _(I)(m,n)=ĥ _(I)(m,n−1)+μA ²(n−m)ε_(I)(n)  [15]

An identical derivation yields the update equations for the Q pathĥ _(Q)(m,n)=ĥ _(Q)(m,n−1)+μA ²(n−m)ε_(Q)(n)  [16]

Each tap or coefficient may be updated according to these equationsleading to the vector notation (or family) of equations:

$\begin{matrix}{\begin{bmatrix}{{\hat{h}}_{I}\left( {0,n} \right)} \\{{\hat{h}}_{I}\left( {1,n} \right)} \\\vdots \\{{\hat{h}}_{I}\left( {M - {1,n}} \right)}\end{bmatrix} = {\begin{bmatrix}{{\hat{h}}_{I}\left( {{0,n} - 1} \right)} \\{{\hat{h}}_{I}\left( {{1,n} - 1} \right)} \\\vdots \\{{\hat{h}}_{I}\left( {M - {1,n} - 1} \right)}\end{bmatrix} + {{\mu\begin{bmatrix}{A^{2}(n)} \\{A^{2}\left( {n - 1} \right)} \\\vdots \\{A^{2}\left( {n - M - 1} \right)}\end{bmatrix}}{ɛ_{I}(n)}}}} & \lbrack 17\rbrack\end{matrix}$

DC Offset & Low Frequency IMD2 Disturbance Modification

The basic estimation algorithm discussed above may fail in somecircumstances in the presence of real world imperfections, specificallydue to non-IM2 DC offsets. Although for WCDMA, which has −3 dB or 50% ofthe total (2-tone) IMD2 power falling at DC (with even a largerproportion for a WCDMA IMD2 power relative to the final baseband power),the inventor of the present invention has determined that other DCoffsets may masquerade as a genuine IMD2 DC component, therebycorrupting the estimates and leading to potentially degradedcancellation performance. The above LMS estimator is based on thefundamental principle that all non IMD effects are uncorrelated with thereference signal. DC is always correlated with DC, regardless of itssource, and hence non IMD2 DC will be correlated with IMD2 DC. If theother DC offsets are large enough, the IM2 estimator will becomeseverely biased with resultant failure of the canceller.

One example solution to the above potential for real world imperfectionsto potentially degrade cancellation performance is to tap off the errorfeedback point after the receiver DC correction system. However, thiswill add substantial latency and complexity to the cancellation path, asnow the dynamics of the DC correction system must be modelled orreplicated within the cancellation path. A more cost effective solutionmay be to introduce a localized DC removal block within the canceller byhigh-pass filtering the error signal prior to its application to theestimation algorithm.

However, the problem is further compounded by the presence of lowfrequency IM2 disturbances arising from un-modelled variations in eitherthe transmit and/or receive gain. For example, due to gain errors inmodelling either or both the transmit and/or receive gain, when thetransmit power target is modified at the slot rate (1.5 kHz) IM2disturbances at 1.5 kHz are introduced to the system. These disturbancescannot be modelled by the canceller as they originate from eithertransmit and/or receive gain errors, or uncertainties, and hence canonly be rejected in a classical closed loop negative feedback typefashion. Any attenuation introduced by the localized DC correction, highpass filter (HPF) at 1.5 kHz will reduce this negative feedbackregulation gain by an amount equal to the HPF attenuation and, hence,compromise the canceller's ability to reject such disturbances. In asimilar fashion, AM-AM distortion incurred in the PA may result inanother source of low frequency IM2 disturbances.

It is important that the selectivity of the HPF be designed carefullysuch that low frequency IM2 disturbances can be adequately rejected bythe canceller. Any localized HPF should have a selectivity thatsimultaneously rejects DC or static offsets (e.g. <100 Hz) whilstminimizing attenuation or rejection at the slot rate (>=1.5 kHz).

Furthermore, selectivity is also critical from the viewpoint of adaptingor training the IMD2 FIR filters. Removal of signal content at anyfrequency will lead to poorer training of the adaptive filter at thesefrequencies. This phenomenon is referred to as ‘persistent excitation’or ‘sufficient excitation’ in the known literature. In simple terms; ifthe objective is to train the adaptive filter in a certain frequencyrange, then the training signal must have sufficient spectral power inthis range. It is unavoidable that the DC signal content must beremoved, as there is no way to distinguish between IM2 DC and non IM2DC. However, in doing so, the removal of other low frequency contentshould be minimized so as to not compromise the training at thosefrequencies. Accordingly, the selectivity of the HPF is paramount toensure the low frequency accuracy of the adaptive filters. This isparticularly important again given that more than 50% of the basebandIM2 power is at low frequencies. As the requirement of sufficientexcitation becomes more important with increasing order and complexityof the adaptive filter, the selectivity of the HPF will also be moreimportant for the extended multi-tap FIR IMD2 model than the classicalsingle-tap, gain based model.

In addition to adequate selectivity, the HPF must be able to reject ortrack out non IMD2 static offsets above a specific minimum (referred toas the low noise amplifier (LNA) input (i/p)) sufficiently fast enoughthat the IMD2 estimator can converge. DC tracking or removal to lessthan a lower value within fractions of a slot (e.g. 100 us) is thusrequired. This is the classic trade-off of filter bandwidth versusselectivity. In summary, the HPF must have sufficient selectivity toadequately reject static DC offsets of, say, a magnitude approximatelyin a range of 1-100 uV (referred to LNA i/p) in fractions of a slotlength (˜100 us) with minimal attenuation at 1.5 kHz.

One example solution described below is to augment the IM2 estimatorwith a LMS DC estimation stage. The local estimation error determinedwithin the estimator block is then subtracted off the LMS DC estimate.The DC estimate equation is provided by:Î _(dc)(n)=Î _(dc)(n−1)+μ_(dc)Δε_(I)(n)  [18]{circumflex over (Q)} _(dc)(n)={circumflex over (Q)}_(dc)(n−1)+μ_(dc)Δε_(I)(n)Where:

Δε is the DC corrected or high pass filtered estimation errorΔε_(I)(n)=ε_(I)(n)−Î _(dc)(n)  [19]Δε_(Q)(n)=ε_(Q)(n)−{circumflex over (Q)} _(dc)(n)and

ε is the original estimation error, i.e. the IM2 cancelled output as perequation [10].

The high-pass filtered error is then used in the basic IM2 adaptivefilter coefficient update equation to provide the modified version:

$\begin{matrix}{\begin{bmatrix}{{\hat{h}}_{I}\left( {0,n} \right)} \\{{\hat{h}}_{I}\left( {1,n} \right)} \\\vdots \\{{\hat{h}}_{I}\left( {M - {1,n}} \right)}\end{bmatrix} = {\begin{bmatrix}{{\hat{h}}_{I}\left( {{0,n} - 1} \right)} \\{{\hat{h}}_{I}\left( {{1,n} - 1} \right)} \\\vdots \\{{\hat{h}}_{I}\left( {M - {1,n} - 1} \right)}\end{bmatrix} + {{\mu\begin{bmatrix}{A^{2}(n)} \\{A^{2}\left( {n - 1} \right)} \\\vdots \\{A^{2}\left( {n - M - 1} \right)}\end{bmatrix}}{{\Delta ɛ}_{I}(n)}}}} & \lbrack 20\rbrack\end{matrix}$with a corresponding equation for the Q-path.

This is equivalent to introducing an IIR based HPF along the estimationerror path between the IM2 cancellation point with ε as the input and Δεas the output having the lead-lag or pole-zero transfer function of:

$\begin{matrix}\frac{1 - z^{- 1}}{1 + \mu_{dc} - z^{- 1}} & \lbrack 21\rbrack\end{matrix}$

The HPF has a zero at z=1 and a pole located at z=1/(1+μ_(dc)).

The digital differentiator term; 1−z⁻¹ removes the static DC whilst thepole can be positioned via a suitable choice of μ_(dc) to affect therequired selectivity versus bandwidth (settling time) trade off. Forexample, as μ_(dc)→∞ the pole→0 and the HPF tends towards a pure digitaldifferentiator. In this case the settling time will be less than ‘1’clock period. However, the selectivity, particularly at a criticalfrequency of 1.5 kHz will be compromised to the extent that lowfrequency IM2 disturbance will be inadequately regulated by the loop.Moreover, training of a multi-tap adaptive filter will be poorer due todiminished spectral content over the stop band of the filter.Conversely, at the other extreme as μ_(dc)→0 the pole tends towardsunity or towards the zero systematically improving selectivity, but at acost of progressively longer settling in order to track out a givenlevel of DC offset. (Obviously for μ_(dc)=0 there is no DC rejection asthe pole cancels with the zero or the settling time is infinite).

It is useful to highlight that the HPF error, Δε(n), is only usedlocally within the LMS estimator whilst the error, ε(n) is used as thecorrected or IM2 cancelled output for the remainder of the radio/modemline-up. In this manner, the HPF effect advantageously only occurswithin the estimator. Instead, if Δε(n) was used as the IM2 cancelledoutput and input to the remainder of the modem the high pass filteringeffect could potentially degrade the signal SNR by removing lowfrequency components of the wanted signal.

Re-Partitioning of Baseband Filter

Referring back to FIG. 4, the principal building blocks and input/outputsignals to/from the example LMS adaptive estimator 458 are illustrated.The cancelled or corrected output, 454, 456 is high pass filtered by theDC estimate-correction stage, 466 and used as the error signal to beapplied to the LMS engine, 468.

In accordance with one example embodiment, the adaptive estimator moduleis arranged to tap off a portion of the baseband transmit signalfollowing adjacent channel interference filtering and prior to a gainstage applying a gain to the filtered baseband receive signal. In thismanner, the derivative or regressor input, A², 444 is tapped off priorto the gain term ĝ_(txrx) 446 and input to adaptive estimator module 458(noting that according to the strict derivation of the equations it maybe tapped off after the gain term). In one example, this departure froma more classic-based approach is adopted for implementation reasons, asA² 444 will have a much reduced dynamic range thereby leading to a morecost effective bit width requirement. In an alternative example, whereA² is tapped out after the gain stage 446, a larger dynamic range isrequired, for example in the order of 50 dB in order to track theautomatic gain control (AGC) range from approximately −110 dBM to −80dBm and a 30 dB range, plus a 2 dB-by-10 dB range to track the outputpower from maximum to approximately 10 dB below). The gain or adaptationrate engine or algorithm can be modified and easily compensated throughthe step-size term, μ, 470, for example in a sense that the gain termmay be considered as being embedded into a step-size. Basically bytapping off 444 prior to 446 it is possible to save on hardware costs asthe fixed point word size requirement is reduced. However, the gainline-up changes as a result, which in one example embodiment may becompensated by modifying the adaptation rate. Gain stage 446 andstep-size term, μ, 470 effect gains within the cancellation loop.Depending upon where the signals are tapped off such gains may affectthe transient response of the loop. Thus, tapping off signal 444 priorto gain stage 446 changes the transient, which in one example embodimentmay be controlled by modifying step-size term, μ, 470. In the describedexample, the step-size or adaptation rate, μ, 470 is generated based onthe current estimate of the on-channel power and fed into the LMS updateengine 458. The update estimates are then fed to their respectivefilters 468 in the cancellation subsystem.

The known art of US2008/0232268 discloses a placement of the digitaladjacent channel interference (ACI) filter after the tapping of theerror signal in the receiver chain. In this manner, the known adaptiveestimator removes or attenuates adjacent channel interference. However,the inventor of the present invention has recognised and appreciatedthat such a design is only reliable in a steady-state, static conditionwith the adaptive filters fully converged, otherwise the delay throughthe receiver line-up is too long in terms of adaptation time for thecanceller. Hence, the known art of US2008/0232268 discloses a suboptimalfilter partitioning that results in an impractical and uneconomicalsolution.

In contrast, in the above described example, a mechanism forindependently trading off ACI rejection versus settling time ispresented. Thus, a novel receiver architecture is provided by locatingthe cancellation point before the ACI filter but with a feedback tappoint located after the ACI filter, in order to partition thecancellation node to provide a more accurate cancellation of IMD2products. As all the blocks/functions included in the line-up up to theactually point of cancellation have to be modelled along thecancellation path, it is preferable to insert the cancellation point andtap off the feed back point as early in the line-up as possible in orderto simplify the cancellation model. In the above example, the ACI filteris modelled as a latency value 460, which has been determined as beingsufficient for cancellation purposes. In particular, the receiverarchitecture partitions the cancellation node across digital basebandfiltering stages, thereby basing the estimate on the current on-channelpower level. In this manner, the estimator is able to converge fasterand therefore reject more noise.

The example receiver architecture may be implemented in a wirelesscommunication unit that comprises a transmitter arranged to process abaseband transmit signal to produce a first radio frequency signal forwireless transmission and a receiver arranged to receive a second radiofrequency signal and convert the second radio frequency signal to abaseband receive signal. The receiver comprises an analogue-to-digitalconverter operably coupled to a summation module arranged to add acancellation signal to the baseband receive signal. The receiver furthercomprises a selectivity element that is arranged to couple thetransmitter and the receiver to an antenna, such that a reduced portionof the first radio frequency signal is introduced into the second radiofrequency signal thereby creating a second order inter-modulationdistortion component in the baseband receive signal. The receiverfurther comprises a digital adjacent channel filter located in thereceiver to filter signals output from the summation module; and anadaptive estimator module arranged to receive the output filteredsignals and the baseband transmit signal and produce the cancellationsignal based thereon.

Adaptation Rate Algorithm

The adaptation rate, μ, 470 controls the rate at which the estimatesconverge and, therefore, the ability of the adaptive estimator 458 toreject noise. The larger the adaptation rate, μ, 471, the faster therate of convergence but the poorer the noise rejection, and vice versa.All received ‘I’ and ‘Q’ signals that are uncorrelated to the transmitAM-squared signal appear as noise to the adaptive estimator 458. As thisnoise level increases, the adaptation rate, μ, 471 should be turned downproportionally. Such uncorrelated noise arises from obvious sources,such as thermal noise in the analogue front end, data converterquantisation noise and also from less obvious sources, such as thewanted receive signal itself, Î_(OR). In addition, IM₃, cross modulationand all other receiver front end impairments will contribute to thisuncorrelated noise. Essentially, all contributors to the totalon-channel signal, except the IMD2 effect and DC offsets, appear asuncorrelated noise. In one example, as this noise floor varies theadaptation rate, μ, 471 is adjusted inversely to retain a desired levelof noise rejection.

The automatic adjustment of the adaptation rate is accomplished by thededicated system 472. In one example, the digital in-band powerdetection of the AGC system is advantageously reused to obtain a dynamicestimate of the on-channel power. The estimated power value is used toindex a look-up table (LUT) 470, whose entries are scaled to provide anadaptation rate that varies inversely with the square root of the powerestimate. In a simplified example the LUT 470 implements a 1/√{squareroot over (x)} function, or more generally the function μ₀/√{square rootover (x)}, where x is proportional to the detected power (V²) and μ₀ isa constant chosen to scale the step-size output to work over thedesignated power range (from sensitivity to approximately −80 dBm). Foron-channel power levels that are determined as being at a receivedsignal power level that is lower than the communication unit's receiversensitivity level, the step-size μ=μ₀ may be used, whilst for powerlevels above the upper limit, μ=0, (i.e. the estimator algorithm isturned ‘off’) and for intermediate levels the rate is arranged to bevaried, for example from μ₀ to 0 in a 1/√{square root over (x)} fashion.

Adaptation Rate Engine

A fixed point implementation of an example adaptation rate block isillustrated in FIG. 4. In the aforementioned examples, it is envisagedthat a typical AGC power detection module, as known in the art, may beused and is thus not described herein further for simplicity purposes.In one example, the LUT 470 may be stored with unsigned, 12 b fractionalvalues that, say, span a 30 dB range from μ₀ to μ₀√{square root over(10^(−30/20))} in a 1/√{square root over (x)} fashion.

In one example, a RAM based LUT 470 is configured to facilitate aprogrammability of μ₀ values. In one example, the LUT 470 may also, as acontingency measure, be configured to facilitate a programmability of1/√{square root over (x)} values if the profile proves inadequate. Inone example, an address scheme employed to access the LUT 470 may bescaled, such that the maximum values is read out when the minimum (orlower) power is detected (e.g. when the receiver is at, or approaching,its sensitivity level, e.g. where Î_(or) is typically approaching −110dBm and Î_(oc) is approaching −102 dBm (principally a thermal noiselevel)). In this example, for power levels within a 30 dB window abovethis minimum (for example at −110 dBm) the LUT 470 may be arranged tooutput a word that is inversely proportional to the square root of thedetected power. For power levels below this upper limit, a zero valuedmay be read out of the LUT 470. Thereafter, this normalised LUT outputmay then be scaled by a programmable gain, μ whose product provides theadaptation rate for the LMS estimator.

Thus, the known art of US2008/0232268 discloses a receiver chain thathas a fixed μ adaptation rate gain. Hence, US2008/0232268 discloses amechanism that cannot adapt to a typical practical situation, forexample where the receive signal may vary dynamically over a large range(say, from ˜−115 dBm to ˜−80 dBm). Thus, the mechanism disclosed inUS2008/0232268 produces a suboptimum performance. Therefore, in oneexample as described above, a novel automatic regulation of adaptationrate is provided in order to provide a more accurate cancellation ofIMD2 products. In particular, the receiver architecture discloses amechanism that automatically scales the adaptation rate gain with thereceive signal power.

The example receiver architecture may be implemented in a wirelesscommunication unit that comprises a transmitter arranged to process abaseband transmit signal to produce a first radio frequency signal forwireless transmission and a receiver arranged to receive a second radiofrequency signal and convert the second radio frequency signal to abaseband receive signal wherein the receiver comprises a summationmodule arranged to add a cancellation signal to the baseband receivesignal. The wireless communication unit further comprises a selectivityelement that is arranged to couple the transmitter and the receiver toan antenna, such that a reduced portion of the first radio frequencysignal is introduced into the second radio frequency signal therebycreating a second order inter-modulation distortion component in thebaseband receive signal. The wireless communication unit furthercomprises a power measurement module arranged to measure an on-channelpower level of the baseband receive signal. The wireless communicationunit further comprises an adaptive estimator module operably coupled tothe power measurement module and arranged to receive the first basebandtransmit signal and the baseband receive signal wherein the adaptiveestimator module comprises a baseband processing module arranged todetermine an adaptation rate to be used by the adaptive estimator modulein generating the cancellation signal based on the measured on-channelpower level of the baseband receive signal.

A paper titled “An integrated LMS adaptive filter of Tx leakage for CDMAreceiver front ends” by Qualcomm and published in the IEE in May 2006proposes a continuous-time, analogue based adaptive interferencecancellation system solution. This document proposes to tap off a radiofrequency reference after the power amplifier and proposes to remove anytransmit leakage prior to a non-linear down-mixing stage, therebypreventing IM2 being generated. Although the underlying principle ofadaptive interference cancellation holds, the known prior art suffersfrom the classical analogue problems of; DC offsets, degraded noisefigure and current consumption

The known techniques focus on calibrating an adaptive IP2 measurementand responding to the calibration, in order to solve the primary problemof limiting the receiver mixer 2^(nd) order intermodulation products.For example, the known art teaches how to tune or calibrate the receiverRF front-end circuits and devices, so as to maximize its IP2 power leveland hence minimize the 2^(nd) order intermodulation products. Incontrast, the proposed technique proposes a cancellation technique.

Time Alignment of Cancellation Signal

Time misalignment between the actual transmit-receive IMD2 path and thecancellation model may occur due to phase mismatch between the analoguefilters and their digital model equivalent. In addition, further timedelay mismatch may occur due to unaccounted for register delays ineither path. Although the adaptive structure of the IMD2-FIR filter may,in some instances, correct for such time misalignment it is not the mostefficient mechanism for compensating for pure latency or constant groupdelay mismatch. For example, by arbitrarily increasing the number oftaps, an arbitrary misalignment can be corrected for. However, thisapproach adds not only further complexity to the actual filter itselfbut also to the adaptive LMS estimator as well as extending itsconvergence time. Accordingly, in some herein described examples, adedicated time alignment block is included to correct for timemisalignment.

In example embodiments, a fixed programmable delay line is included inboth the cancellation path, {circumflex over (D)} and the actualtransmit or receive IMD2 path, D₀. Inclusion of a delay, D₀, asillustrated by delay 440 along the cancellation path of FIG. 4, alongthe actual transmit-receive path covers the eventuality of where thecancellation path delay is longer than the actual delay. In FIG. 4, thedelay, D₀ 440 is illustrated as being inserted between the receiverADC-CIC and the IMD2 cancellation node.

An adaptive IMD2 FIR filter structure is included to track out filtermis-modelling and filter variations, as well as correct for a limitedrange of unknown time misalignments. In principle, by extending the tapcount it is possible to correct for time misalignments of arbitrarylength. However, given that such misalignment will be dominated byunknown but fixed digital time delays, which will only need to becorrected once, such an approach (i.e. increased FIR tap count), ishardware inefficient. Instead a dedicated self-tuning time alignmentsystem is included for this purpose.

Referring now to FIG. 7, and in order to complement the fixed delaysynchronisation, a self-tuning delay mechanism 700 is included that isarranged to dynamically adjust the programmable delay value {circumflexover (D)}_(c) with {circumflex over (d)}_(c) so as to equalise the pathdelays. A composite delay from both paths, provided by summing logic735, is then applied to the tapped delay line 440 in an integer andfractional format via an integer/fraction module 736, as shown.

Self-Tuning Time Alignment System

A firmware or hardware based implementation, or asoftware/firmware-based tuning algorithm, is based on an extension tothe principle of peak correlation. The basic principle in the example ofa self-tuning alignment system is based on the fact that if the timemisalignment between the actual output and the estimated output iskT_(s), where T_(s), is the common underlying sampling period, then thecorresponding cross correlation will be a maximum or peak at lag k. Thetime misalignment is then measured by resolving the cross correlation toa fine enough accuracy and establishing at what lag value thecorrelation is a maximum. However this conventional application of theprinciple can lead to a hardware inefficient implementation that isarguably as costly as increasing the adaptive FIR filter tap count. Forexample, in order to resolve the misalignment to better than 1/16^(th)of a chip period over a range of +/−2 chips would require 2×16×2multiple and add structures.

An alternative approach described herein evaluates the cross correlationat only 4 lag values. These values are then combined (using equation[23] in logic/function module 728) to provide an error type functionthat has an approximate linear relationship with the time misalignment.The error function is then used to drive a simple digital controller730, which adjusts the delay 440 in the digital tapped time alignment soas to minimize this error.

More specifically, in this example and assuming the time misalignment islimited to a range of +/−2 chips, the cross correlation at lag values of+/−1 chip (using a first delay 460) and +/−2 chips will suffice (usingtwo delays 460). The cross correlation function in determining a crosscorrelation value between a sample WCDMA amplitude squared signal andits delayed value for lag values of +/−1 and +/−2 chips respectively isrelated to the pulse response of the SRRC filter 714 used in thegeneration of the WCDMA signal. In this manner, a maximum or peak thatis clearly evident, where the lag equals the time misalignment and fallsoff in a SRRC pulse type fashion, is used as the misalignment deviatesfrom zero.

Let us define the normalized cross correlation at +1 chip advance asr_(xy)(1) and at 1 chip lag or delay as r_(xy)(−1). Let us furtherdefine a function that is approximately proportional to the timemisalignment value within a window of +/−1 chip period from:ε=r _(xy)(−1)−r _(xy)(1)  [22]

This error function behaves well within a range of +/−1 chip, butdegrades beyond that point and eventually takes on the wrong sign as themisalignment approaches +/−2 chips. To improve the error functionaccuracy over a +/−2 chip range one example embodiment modifies theerror equation by incorporating the cross correlation function at +/−2chip lag (using logic/function module 728) as follows:ε=r _(xy)(−1)−r _(xy)(1)+r _(xy)(−2)−r _(xy)(2)  [23]

The resultant error function sign is now correct over the +/−2 chipmisalignment window. It is possible to further improve the linearrelationship of the error function to the time misalignment over anarbitrary window at the expense of additional cross correlation lagentries. However, assuming the timing misalignment is limited to +/−2chips, then the error function of equation [23] composed of lags at +/−1chip and +/−2 chips is accurate enough to drive the subsequent controlloop.

In this example, four delayed versions 716, 462, 463, 466 of theamplitude squared signal, A² are generated corresponding to the signaladvanced by 2 chips, advanced by 1 chip, delayed by 1 chip and delayedby 2 chips, i.e. the vector of variables are generated as provided inequation [24];{A²(n+2L)A²(n+L)A²(n−L)A²(n−2L)},  [24]where:

n is the current index and

L is an index offset corresponding to 1 chip period.

In practice, given that the SRRC filter 714 along the cancellation pathin this example is implemented as an FIR filter of the form:

$\begin{matrix}{{{A^{2}(n)} = {\sum\limits_{k = 0}^{N - 1}{c_{k}{A_{i}^{2}\left( {n - k} \right)}}}},} & \lbrack 25\rbrack\end{matrix}$where:

A_(i) ² is the SRRC input amplitude squared signal and

c_(k) is the k^(th.) Coefficient of the SRRC filter 714,

an approximation to the advanced signals, A²(n+2L) and A²(n+L) will beavailable from the regressor or delay line employed within the SRRCfilter itself.

In particular, if the SRRC is designed to run at Lx the chip rate,tapping off the internal regressor 2L and L from the end of the delayline, i.e. A_(i) ²(n−N+2L+1), A_(i) ²(n−N+L+1) yields an approximationto the advanced signals A²(n+2L) and A²(n+L). The actual output of theSRRC filter 714 is delayed by additional delay elements to produced thedelayed or lagged values A²(n−L) and A²(n−2L) Depending on the order ofthe adaptive IMD2-FIR filter, these delay values 460 may already beavailable from the adaptive FIR regressor delay line.

The DC component from of an amplitude squared regressed vector and theerror amplitude is then removed via the digital differentiator, 722,462, 463 and 466 before the correlation step, as such offsets that areunrelated to time misalignment and could dominate the correlationresult, and hence degrade the overall accuracy. The notation x₂ is usedto represent the DC notched, 2 chip advanced amplitude squared signal,x₁ the corresponding single chip advanced signal, x⁻¹ the single chipdelayed and x⁻² the 2 chip delayed signal. y is used to represent the DCnotched amplitude square error signal.

An integrate-and-dump function/module 726, 720, 710, 706 is then appliedto the product 724, 718, 708, 704 of each of these delay terms; {x₂, x₁,x⁻¹, x⁻²} and y to effect the desired correlation operation. Theintegration window length, N, in one example, is programmable andextends over a programmable binary fraction of a slot length, such as1/16^(th), ⅛^(th), ¼^(th), ½, 1, and 2.

The error function in equation [23] from logic/module 728 is thengenerated from the respective cross correlation terms at the integrateand dump output rate and applied to a basic integral controller 730.{circumflex over (d)}(n)={circumflex over (d)}(n−1)+μ_(D)ε(n)  [26]where:

{circumflex over (d)}(n) is the corrected or update for the self-tunedtime alignment estimate, and

μ_(D) is an adaptation rate which scales with detected on-channel power.

In a similar manner to the use of the step-size term, μ, 470, in FIG. 4where the adaptation rate is scaled inversely with the square root ofthe on-channel power, the control equation may also be scaled withrespect to square root of the on-channel power as described previously.

The delay estimate {circumflex over (d)} 733 is added to theprogrammable delay estimate, {circumflex over (D)}_(c) 734 to providethe composite delay, which is then decomposed into its integer andfractional components in integer/fraction logic/module 736 and appliedto the delay 440 in the cancellation delay line.

In a yet further example embodiment, a limiting scheme may be employedwhere the estimate, {circumflex over (d)} is constrained within theboundary: −{circumflex over (D)}_(c)≦{circumflex over(d)}≦max{{circumflex over (D)}}−{circumflex over (D)}_(c), wheremax{{circumflex over (D)}} is the upper limit of the delay line. In thisexample, an option of extending below the lower bound, −{circumflex over(D)}_(c) may be available by increasing the intentional delay, D₀ alongthe actual transmit-receive, IMD2 path, i.e. instead of reducing thecancellation delay by decreasing {circumflex over (d)} below−{circumflex over (D)}_(c), the intentional transmit-receive delay maybe increased. This implementation is preferably programmable to avoidvarying the actual transmit or receive path delay at certain timeinstances, for example during a live call.

Thus, the prior art of US2008/0232268 discloses a peak detector thatselects a lag value to time align the cancellation signal, where amaximum cross correlation value is determined in order to align twosignals. However, such known prior art provides for only a roughcorrection for group delay variation due to analogue filter uncertaintyin the receiver. Thus, in one example, a novel time alignment system tocorrectly time align the cancellation signal has been described. Inparticular, a self tuning time alignment system has been described toaccommodate for group delay variation due to analogue filter uncertaintyin the receiver by use of an error function and associated controller toperform time alignment of the cancellation signal.

The example self tuning time alignment system may be implemented in awireless communication unit that comprises a transmitter arranged toprocess a first baseband transmit signal to produce a first radiofrequency signal for wireless transmission, and a receiver arranged toreceive a second radio frequency signal and convert the second radiofrequency signal to a baseband receive signal wherein the receivercomprises a summation module arranged to add a cancellation signal tothe baseband receive signal. The communication unit further comprises aselectivity element that is arranged to couple the transmitter and thereceiver to an antenna. A reduced portion of the first radio frequencysignal is introduced into the second radio frequency signal therebycreating a second order inter-modulation distortion component in thebaseband receive signal. The communication unit further comprises acontroller module arranged to perform cross-correlation of at least onetap of each of the first baseband transmit signal and the cancellationsignal to produce an error signal that is representative of a timedifference therebetween. A controllable delay element is operablycoupled to the controller module and arranged to use the error signal toset a time delay applied to at least one from a group of: the firstbaseband transmit signal, the cancellation signal.

Although some aspects of the invention have been described withreference to their applicability to second order intermodulationdistortion cancellation in a wireless communication unit that supportsUMTS (Universal Mobile Telecommunication System) cellular communicationsystem and in particular to a UMTS Terrestrial Radio Access Network(UTRAN) of a 3^(rd) generation partnership project (3GPP) system, itwill be appreciated that the invention is not limited to this particularcellular communication system. It is envisaged that the conceptdescribed above may be applied to any other wireless communicationsystem or technology.

Referring now to FIG. 8, there is illustrated a typical computing system800 that may be employed to implement signal processing functionality inembodiments of the invention. Computing systems of this type may be usedin access points and wireless communication units. Those skilled in therelevant art will also recognize how to implement the invention usingother computer systems or architectures. Computing system 800 mayrepresent, for example, a desktop, laptop or notebook computer,hand-held computing device (PDA, cell phone, palmtop, etc.), mainframe,server, client, or any other type of special or general purposecomputing device as may be desirable or appropriate for a givenapplication or environment. Computing system 800 can include one or moreprocessors, such as a processor 804. Processor 804 can be implementedusing a general or special-purpose processing engine such as, forexample, a microprocessor, microcontroller or other control module. Inthis example, processor 804 is connected to a bus 802 or othercommunications medium.

Computing system 800 can also include a main memory 808, such as randomaccess memory (RAM) or other dynamic memory, for storing information andinstructions to be executed by processor 804. Main memory 808 also maybe used for storing temporary variables or other intermediateinformation during execution of instructions to be executed by processor804. Computing system 800 may likewise include a read only memory (ROM)or other static storage device coupled to bus 802 for storing staticinformation and instructions for processor 804.

The computing system 800 may also include information storage system810, which may include, for example, a media drive 812 and a removablestorage interface 820. The media drive 812 may include a drive or othermechanism to support fixed or removable storage media, such as a harddisk drive, a floppy disk drive, a magnetic tape drive, an optical diskdrive, a compact disc (CD) or digital video drive (DVD) read or writedrive (R or RW), or other removable or fixed media drive. Storage media818 may include, for example, a hard disk, floppy disk, magnetic tape,optical disk, CD or DVD, or other fixed or removable medium that is readby and written to by media drive 812. As these examples illustrate, thestorage media 818 may include a computer-readable storage medium havingparticular computer software or data stored therein.

In alternative embodiments, information storage system 810 may includeother similar components for allowing computer programs or otherinstructions or data to be loaded into computing system 800. Suchcomponents may include, for example, a removable storage unit 822 and aninterface 820, such as a program cartridge and cartridge interface, aremovable memory (for example, a flash memory or other removable memorymodule) and memory slot, and other removable storage units 822 andinterfaces 820 that allow software and data to be transferred from theremovable storage unit 818 to computing system 800.

Computing system 800 can also include a communications interface 824.Communications interface 824 can be used to allow software and data tobe transferred between computing system 800 and external devices.Examples of communications interface 824 can include a modem, a networkinterface (such as an Ethernet or other NIC card), a communications port(such as for example, a universal serial bus (USB) port), a PCMCIA slotand card, etc. Software and data transferred via communicationsinterface 824 are in the form of signals which can be electronic,electromagnetic, and optical or other signals capable of being receivedby communications interface 824. These signals are provided tocommunications interface 824 via a channel 828. This channel 828 maycarry signals and may be implemented using a wireless medium, wire orcable, fiber optics, or other communications medium. Some examples of achannel include a phone line, a cellular phone link, an RF link, anetwork interface, a local or wide area network, and othercommunications channels.

In this document, the terms ‘computer program product’‘computer-readable medium’ and the like may be used generally to referto media such as, for example, memory 808, storage device 818, orstorage unit 822. These and other forms of computer-readable media maystore one or more instructions for use by processor 804, to cause theprocessor to perform specified operations. Such instructions, generallyreferred to as ‘computer program code’ (which may be grouped in the formof computer programs or other groupings), when executed, enable thecomputing system 800 to perform functions of embodiments of the presentinvention. Note that the code may directly cause the processor toperform specified operations, be compiled to do so, and/or be combinedwith other software, hardware, and/or firmware elements (e.g., librariesfor performing standard functions) to do so.

In an embodiment where the elements are implemented using software, thesoftware may be stored in a computer-readable medium and loaded intocomputing system 800 using, for example, removable storage drive 822,drive 812 or communications interface 824. The control module (in thisexample, software instructions or computer program code), when executedby the processor 804, causes the processor 804 to perform the functionsof the invention as described herein.

In particular, it is envisaged that the aforementioned inventive conceptcan be applied by a semiconductor manufacturer to any integrated circuitcomprising transceiver modules, for example those of the MediaTek™MT6162 transceiver IC family and those of the MediaTek™ MT6573 andMT6276, baseband processor family.

Furthermore, the inventive concept may be applied in anapplication-specific integrated circuit (ASIC) and/or any othersub-system element or one or more circuits.

It will be appreciated that, for clarity purposes, the above descriptionhas described embodiments of the invention with reference to differentfunctional units and processors. However, it will be apparent that anysuitable distribution of functionality between different functionalunits or processors, for example with respect to the beamforming moduleor beam scanning module, may be used without detracting from theinvention. For example, functionality illustrated to be performed byseparate processors or controllers may be performed by the sameprocessor or controller. Hence, references to specific functional unitsare only to be seen as references to suitable means for providing thedescribed functionality, rather than indicative of a strict logical orphysical structure or organization.

Aspects of the invention may be implemented in any suitable formincluding hardware, software, firmware or any combination of these. Theinvention may optionally be implemented, at least partly, as computersoftware running on one or more data processors and/or digital signalprocessors or configurable module components such as FPGA devices. Thus,the elements and components of an embodiment of the invention may bephysically, functionally and logically implemented in any suitable way.Indeed, the functionality may be implemented in a single unit, in aplurality of units or as part of other functional units.

Although the present invention has been described in connection withsome embodiments, it is not intended to be limited to the specific formset forth herein. Rather, the scope of the present invention is limitedonly by the accompanying claims. Additionally, although a feature mayappear to be described in connection with particular embodiments, oneskilled in the art would recognize that various features of thedescribed embodiments may be combined in accordance with the invention.In the claims, the term ‘comprising’ does not exclude the presence ofother elements or steps.

Furthermore, although individually listed, a plurality of means,elements or method steps may be implemented by, for example, a singleunit or processor. Additionally, although individual features may beincluded in different claims, these may possibly be advantageouslycombined, and the inclusion in different claims does not imply that acombination of features is not feasible and/or advantageous. Also, theinclusion of a feature in one category of claims does not imply alimitation to this category, but rather indicates that the feature isequally applicable to other claim categories, as appropriate.

Furthermore, the order of features in the claims does not imply anyspecific order in which the features must be performed and in particularthe order of individual steps in a method claim does not imply that thesteps must be performed in this order. Rather, the steps may beperformed in any suitable order. In addition, singular references do notexclude a plurality. Thus, references to ‘a’, ‘an’, ‘first’, ‘second’,etc. do not preclude a plurality.

Thus, an improved integrated circuits, communication units and methodstherefor have been described, wherein the aforementioned disadvantageswith prior art arrangements have been substantially alleviated.

1. A wireless communication unit comprising: a transmitter arranged toprocess a quadrature baseband transmit signal to produce a first radiofrequency signal for wireless transmission, a receiver arranged toreceive a second radio frequency signal and convert the second radiofrequency signal to a quadrature baseband receive signal, wherein thereceiver comprises at least one summation module arranged to add acancellation signal to the quadrature baseband receive signal; aselectivity element that is arranged to couple the transmitter and thereceiver to an antenna, such that a reduced portion of the first radiofrequency signal is introduced into the second radio frequency signalthereby creating a second order inter-modulation distortion component inthe baseband receive signal; and a baseband processing module arrangedto: receive the quadrature baseband transmit signal and quadraturebaseband receive signal; apply independent gain and phase adjustments toquadrature portions of the quadrature baseband transmit signal, based onat least one signal component of the quadrature baseband receive signal,to form independent cancellation signals; and apply the independentcancellation signals to the at least one summation module.
 2. Thewireless communication unit of claim 1 wherein the baseband processingmodule comprises a plurality of independent adaptive filters.
 3. Thewireless communication unit of claim 2 wherein the plurality ofindependent adaptive filters comprise multi-tap finite impulse response(FIR) filters arranged to compensate for a mismatch error between thequadrature baseband receive signal and the quadrature baseband transmitsignal.
 4. The wireless communication unit of claim 1 furthercomprising: a power measurement module operably coupled to the adaptiveestimator module arranged to measure an on-channel power level of thebaseband receive signal; and wherein the adaptive estimator modulecomprises a baseband processing module arranged to determine anadaptation rate to be used by the adaptive estimator module ingenerating the cancellation signal based on the measured on-channelpower level of the baseband receive signal.
 5. The wirelesscommunication unit of claim 4 wherein the baseband processing module isarranged to ignore uncorrelated noise components such that thecancellation signal cancels second order intermodulation distortioncomponent.
 6. The wireless communication unit of claim 1 wherein thereceiver comprises an analogue-to-digital converter operably coupled tothe summation module further comprising: a digital adjacent channelfilter located in the receiver and arranged to filter signals outputfrom the summation module; and wherein the adaptive estimator module isarranged to receive the output filtered signals and the basebandtransmit signal and produce the cancellation signal based thereon. 7.The wireless communication unit of claim 6 wherein the digital filter isa digital adjacent channel filter.
 8. The wireless communication unit ofclaim 7 wherein the digital adjacent channel filter comprises a matchingfilter.
 9. The wireless communication unit of claim 1 furthercomprising: a controller module arranged to perform cross-correlation ofat least one tap of each of the first baseband transmit signal and thecancellation signal to produce an error signal that is representative ofa time difference therebetween; a controllable delay element operablycoupled to the controller module and arranged to use the error signal toset a time delay applied to at least one from a group of: the firstbaseband transmit signal, the cancellation signal.
 10. The wirelesscommunication unit of claim 9 wherein the controller module is arrangedto perform cross correlation between two signals evaluated at a numberof Lag points.
 11. The wireless communication unit of claim 9 whereinthe controller module is arranged to adjust the controllable delayelement until the error signal is at a minimum.
 12. An integratedcircuit for a wireless communication unit comprising: a transmitterarranged to process a quadrature baseband transmit signal to produce afirst radio frequency signal for wireless transmission, a receiverarranged to receive a second radio frequency signal comprising a reducedportion of the first radio frequency signal and convert the second radiofrequency signal to a quadrature baseband receive signal, wherein thereceiver comprises at least one summation module arranged to add acancellation signal to the quadrature baseband receive signal, andwherein the reduced portion of the first radio frequency signal createsa second order inter-modulation distortion component in the basebandreceive signal; and a baseband processing module arranged to: receivethe quadrature baseband transmit signal and quadrature baseband receivesignal; apply independent gain and phase adjustment to quadratureportions of the quadrature baseband transmit signal, based on at leastone signal component of the quadrature baseband receive signal, to formindependent cancellation signals; and apply the independent cancellationsignals to the at least one summation module.
 13. The integrated circuitof claim 12 wherein the baseband processing module comprises a pluralityof independent adaptive filters.
 14. The integrated circuit of claim 13wherein the plurality of independent adaptive filters comprise multi-tapfinite impulse response (FIR) filters arranged to compensate for amismatch error between the quadrature baseband receive signal and thequadrature baseband transmit signal.
 15. A method for reducing a secondorder inter-modulation distortion component in a wireless communicationunit, the method comprising: processing a quadrature baseband transmitsignal to produce a first radio frequency signal for wirelesstransmission; receiving a second radio frequency signal comprising areduced portion of the first radio frequency signal that creates asecond order inter-modulation distortion component in the basebandreceive signal; converting the second radio frequency signal to aquadrature baseband receive signal; applying independent gain and phaseadjustments to quadrature portions of the quadrature baseband transmitsignal, based on at least one signal component of the quadraturebaseband receive signal, to form independent cancellation signals; andadding the independent cancellation signals to the quadrature basebandreceive signal to reduce the second order inter-modulation distortioncomponent.
 16. The method of claim 15 further comprising compensatingfor a mismatch error between the quadrature baseband receive signal andthe quadrature baseband transmit signal by setting a plurality ofmulti-tap finite impulse response (FIR) filters.
 17. A computer programproduct comprising executable program code for reducing a second orderinter-modulation distortion component in a wireless communication unit,the executable program code operable for: processing a quadraturebaseband transmit signal to produce a first radio frequency signal forwireless transmission; receiving a second radio frequency signalcomprising a reduced portion of the first radio frequency signal thatcreates a second order inter-modulation distortion component in thebaseband receive signal; converting the second radio frequency signal toa quadrature baseband receive signal; applying independent gain andphase adjustments to quadrature portions of the quadrature basebandtransmit signal, based on at least one signal component of thequadrature baseband receive signal, to form independent cancellationsignals; and adding the independent cancellation signals to thequadrature baseband receive signal to reduce the second orderinter-modulation distortion component.
 18. The computer program productof claim 17 where the code is further operable for compensating for amismatch error between the quadrature baseband receive signal and thequadrature baseband transmit signal by setting a plurality of multi-tapfinite impulse response (FIR) filters.
 19. The computer program productof claim 17, wherein the computer program product comprises at least oneof a hard disk, a CD-ROM, an optical storage device, a magnetic storagedevice, a ROM (Read Only Memory), a PROM (Programmable Read OnlyMemory), a EPROM (Erasable Programmable Read Only Memory), an EEPROM(Electrically Erasable Programmable Read Only Memory) and a Flashmemory.